Our Story
In 2022, as experienced sonographers, Emily and Jo began closely examining the accuracy of third-trimester growth scans. We were surprised by the lack of a reliable, standardised method to assess the accuracy of estimated fetal weight (EFW) predictions, both locally and nationally. The primary benchmark for evaluating accuracy remained the detection rate of babies born below the 3rd centile. While this metric had its merits, it felt inadequate—it didn’t fully reflect the accuracy of the scans. For instance, if we consistently under-measured all babies, we could achieve high detection rates yet still be inaccurate, leading to unnecessary interventions such as induction of labour or caesarean. These interventions carry risks and place a significant financial burden on healthcare services.
Another available approach was retrospective image auditing, which is highly subjective and time-consuming. When we reached out to other hospitals, we found widespread inconsistencies in how growth scan accuracy was assessed across different trusts.
Frustrated by this, we set out to improve accuracy rates in our own Trust. However, we quickly realised we lacked an effective way to measure the impact of any changes we were making. This triggered a deeper exploration of the evidence used to guide growth scans, and we were surprised to find how small the patient cohorts often were and how weak the supporting evidence could be.
Given the vast amount of patient data routinely collected, it became clear that there had to be a better, more data-driven solution. With the help of Emily’s husband, Pete, a data scientist, we developed a new, more effective method for evaluating growth scan accuracy, which led to the creation of TAGSA (Tool for Assessing Growth Scan Accuracy).
As we began sharing TAGSA’s progress with our Senior Management team and other Trusts, it became evident that there was a significant appetite for this tool. It wasn’t just about solving a problem for our team—there was a clear need for a wider application across the NHS.
This realisation drove us to create an even more comprehensive toolkit, the Antenatal Sonography Toolkit (AST), designed to help teams effectively assess their growth scan accuracy at both a departmental and individual clinician level. The AST can also be used as a tool to assess quality improvement initiatives and pinpoint root causes of inaccuracy. Our vision is to use the AST to develop a new, more effective, and clinically useful national benchmark for growth scan accuracy.
By this point, it had become clear that the level of statistical modelling required to develop the AST was highly complex, necessitating specialised data science expertise. To ensure the project's integrity and maintain full control over its direction, we made the decision to fund it independently, founding a company to develop and deliver this solution that we are so passionate about.